(1)CLS, 8-10 rue Hermes, Parc Technologique du Canal, 31520 RAMONVILLE SAINT-AGNE, France, jlebras@cls.fr (2)CLS, 8-10 rue Hermes, Parc Technologique du Canal 31520 RAMONVILLE SAINT-AGNE, France, jdumont@cls.fr

(3)CLS, 8-10 rue Hermes, Parc Technologique du Canal 31520 RAMONVILLE SAINT-AGNE, France, rberland@cls.fr (4)BOOST Technologies, 115 rue Claude Chappe, 29 280 PLOUZANE,vincent.kerbaol@boost-technologies.fr

ABSTRACT

In the frame of ESA GSE MARISS project, the objective of the open sea service is to identify friend vessels in the SAR maritime picture and to map the presence of potential threats close to friend vessels, to allow users to improve the awareness of maritime threats in its area of competence. For this goal, CLS has set-up an end-to-end processing chain, which integrates the SARTool© software, developed by BOOST Technologies and targeted at extracting marine information from SAR images, and is based on its operational system used to monitor illegal fishing in the Indian Ocean. ENVISAT SAR scenes (narrow swath, IS6 submode, HH polarization) were acquired, processed at Level 1b (ASA_IMP products) and provided by Kongsberg Satellite Services (KSAT) Grimstad station in August 2006, in order to test the open sea chain behaviour in boundary conditions, close to coastal areas. On French MRCC request, a dangerous and sensitive area within a Traffic Separation Scheme in the English Channel was monitored. Features of the detected ships (estimated location, size, heading and speed) were provided to the user. Results were compared with the characteristics of ships provided by a VTMS system, leading to a positive statement by the user for the interest of the satellite imagery for maritime security, in terms of reliability, location and heading accuracy. In addition, several positive coupling of echoes with VMS data were demonstrated and an oil spill suspected in this non optimal SAR configuration for oil detection was further analysed by BOOST Technologies. This paper eventually discusses potential methods to improve the service chain based on this test case. 1. INTRODUCTION

The MARISS project, part of the GMES1 European programme, has been set up by ESA as one of the consolidation projects of the GMES Services Element to demonstrate preoperational and autonomous European capacity and services for maritime security. Trials in Atlantic and English Channel were part of 1 Global Monitoring for Environment and Safety

several campaigns made in 2006 in order to demonstrate and evaluate improvements of illegal activities monitoring by satellite. 2. OBJECTIVES OF TRIALS IN FRANCE

The chain set-up in 2006 by CLS aimed to provide the French Maritime Affairs with an information product integrating SAR derived ship position and size data with simultaneous VMS transponder data. The objective was to identify friend vessels in the SAR maritime picture and to map the presence of potential threats close to friend vessels, so as to allow responsible authorities to improve the awareness of maritime threats in its area of competence and perform optimum planning of patrolling aircrafts missions. A summary of these trials is presented in this paper, including a validation trial in differed time and examples of near real time operation. 3. SERVICE CHAIN

The service chain is illustrated in Fig.1

Figure 1 : Service chain architecture After acquisition of SAR images and VMS data , ship detection on the SAR image using the SARTool© Ships detection module developed by BOOST, while the backend processing consists of two CLS products: SCOPE© for SAR passes screening and echo classification, META© for fusion with VMS.

Space Agencies

Satellite swath

RADARSAT

NOAA/Argos

ENVISAT

SAR

raw

data

Acquisition

orders and

feedback

Receptionstations

SAR/VMSIntegration

.

-Ship

info

User

Control

centre

Alarms

SAR

report

analysis

AcquisitionProgramming

SAR

processed

data SAR

VMS

integration

CLS

VMS reports

Ship info

Ship info

Commands

SCOPE

META

Satellite swath

RADARSAT

NOAA/Argos

ENVISAT

SAR

raw

data

Acquisition

orders and

feedback

Acquisition

orders and

feedback

Receptionstations

SAR/VMSIntegration

.

-Ship

info

User

Control

centre

Alarms

SAR

report

analysis

AcquisitionProgrammingAcquisitionProgramming

SAR

processed

data SAR

VMS

integration

CLS

VMS reports

Ship info

Ship info

Commands

SCOPE

META

SHIP DETECTION TRIALS WITH ENVISAT ASAR IN THE ENGLISH CHANNEL: COUPLING TESTS WITH VMS AND VTMS

Jean-Yves Le Bras (1), Jean-Paul Dumont (2), Rémi Berland (3), Vincent Kerbaol (4)

_____________________________________________________

Proc. ‘Envisat Symposium 2007’, Montreux, Switzerland 23–27 April 2007 (ESA SP-636, July 2007)

4. NON REAL TIME TEST

For one of the validation tests in non real time, a SAR image was downloaded from the ESA KIRUNA web site on 17 July 2006.

� SAR mode Wide Swath � Pixel resolution 75m x 75m � Polarization VV

The following image shows a geo-located overview of the SAR image:

Figure 1: ENVISAT image used for validation Ship location data was made available in real time for ships fishing or cruising in the Channel and the North Sea. The visualisation of the targets detected on the SAR image and the VMS ship locations was realised using META© (see Fig.2) The boundaries of the SAR image and the targets (the stars on the map) are in red. The VMS ship locations (and the straight lines connecting those locations) are in black. The estimated ship locations at “image acquisition time” are pinpointed by blue logos representing a facing ship. The blue and yellow zones represent the approximate boundaries of the French maritime operation centres (respectively CROSS Jobourg and CROSS Griz-Nez). The following screenshot shows the route (black line) taken by a VMS-identified ship, going from the Channel to the North Sea.

Fig.2 : Fusion of VMS and SAR data

META© allows to display the ship name and the coordinates of the estimated ship position, as well as the coordinates and quick views of targets around it.

Figure 3: Correlation of ship route and SAR echo

A zoom on the estimated ship position shows a distance of about 0.27 miles (500m) to the closest target. So far, no matching can be performed.

Figure 4: Zoom on raw trajectory

META does not take heading information into account when it estimates the ship position. In fact, it draws straight lines between the ship positions and places the estimated ship position on such a line, taking only into account the VMS positions and times. After analysis of VMS messages, we noticed however that the ship heading changed before and after the radar image acquisition (around 10 July 2006, 10:11:19 UTC), and that the heading information was missing for the closest message.

Figure 5: VMS message detail

The missing value can then be replaced by the heading value provided by SARTool© for that target, which is 39.3 degrees, and the heavy traffic maritime picture may explain the temporary direction change ( from 41 to 31 degrees, and back to 41 degrees).

Figure 6: Ship parameters computed by SARTool©

So it could be assumed that the ship did not change direction before the SAR image taking and compute a more accurate interpolated ship position, which is much closer to the target. The distance between the new interpolated position and the target is now about 0.15 mile (275 meters).

Figure 7: Interpolation bias correction

In addition, since the ship is moving (VMS messages indicate a speed of about 13 knots), there is a shift (on the azimuth axis) between the target position detected by SARTool© on the SAR image and the real ship position. The azimuth shift is obtained using the formula (see also the figure below):

sY V

uH ϕθ costan ×−=∆

where H is the altitude of the satellite, θ the SAR incidence angle for the target, u the velocity of the target, ϕ the direction of the target (see figure below),

and sV the azimuth velocity of the satellite.

Satellite

Target velocity

Y, Azimuth

X, Range O Real ship position

ϕ

Detected target position

Y∆

)0,sin,cos( ϕϕ uuu→

Z

θ

Figure 8: Azimuth shift computation

In our case, we have approximately:

kmH 800= , deg19.29=θ , knotsu 13= ,

deg6.117−=ϕ , 17450 −= msVs .

Hence, the azimuth shift is about +200 meters, which indicates that the real ship position on the SAR image is bound to be located about 200 meters (2.66 pixels) below the echo position (i.e. in opposite direction to the azimuth). On the SAR image, however, the target is spread over a bright echo of about 4 pixels x 5 pixels (300 meters x 375 meters!). As one may notice on the following screenshot, SARTool© places the target position almost at the “top” (following the azimuth axis) of the echo.

Figure 9: Target detection using SARTool©

Taking into account the azimuth shift, which is coherent with the ship wake we can see on the screenshot, we may now correct this placement, and move the target location 2 or 3 pixels below the one given by SARTool©. On the figure below, the red, large cross represents the corrected target position.

Figure 10: Final estimation of ship position

The difference between the estimated ship position and the corrected target position shrinks to about 0.05 mile (95 meters), which matches our validation criterion for the fusion in the ENVISAT medium resolution context. 5. REAL TIME EXPERIMENTATION ZONE

ENVISAT SAR scenes (narrow swath, IS6 submode, HH polarization) have been acquired, processed at Level 1b (ASA_IMP products) and provided by KSAT station between August, 16 and September, 04 2006. 7 segments of 4 scenes have been selected: 4 nominal segments and 3 segments as backup solutions, as illustrated in Fig.11

Fig. 11. Location of the experimentation zone

6. TRIAL IN CASQUETS TRAFFIC

SEPARATION SCHEME

The “Casquets” traffic separation scheme has been superposed on this satellite image acquired in August 17th., as shown in Fig.12.

Figure 12: ENVISAT image in Casquets TSS

Parameters of the detected ships (estimated location, size, heading and speed) were provided to the corresponding French MRCC (Cross Jobourg). The false echoes, represented in red correspond to secondary lobes of point target response of the radar. Ships for which features are not complete are represented in yellow. Note also that locations provided in the table account as far as possible for a Doppler azimuth shift with respect to the echo position (as illustrated for ship n°79).

Figure 13: Azimuth ambiguities (general)

Figure 14: Detail on a very bright target

Results are summarised below together with a comparison of the characteristics of ships provided by Cross Jobourg, as extracted from its VTMS:

Shipindex

Lat. Lon.Wake

visibilityHeading

Azimuth shift (m)

Length(m)

Speed (knots)

Length(m)

Speed (knots)

Name IMO N° Type

83 49°49"46' 2°56"11' No 98 - 125 - 129 13.8 TARNLAND 9121699Transport of

various products (TPD)

79 49°50"11' 2°53"42' Yes 58 698 187 22.9 158 19.2 AGLAIA 9216 353Classical Cargo

(GG)

71 49°49"00' 2°51"44' Yes 59 735 240 23.7 250 13.5 GLENBULK A 7915620Oil-bulk-ore ship

(CBO)

72 49°47"52' 2°50"44' No 90 560 78 14 97 9 GURYEV 8700149Transport of

various products (TPD)

73 49°48"08 2°49"43' No 50 - 115 - 78 12 BUKANIER 9195389Classical Cargo

(GG)

59 49°51"00' 2°36"50' Yes 74 774 170 20.8 180 16.1 EIJIN 82023 29Transport of

vehicules (MVE)

88 49°52"34' 2°34"39' Yes 74 780 - 20.9 160 14.7 GINGA COUGAR 9321861Chemical tanker

(TCH)

Information provided by the clientOutputs from the service chain

Figure 14: External verification

The results were stated satisfactory by the Cross with regard to reliability, location and heading, simply exhibiting a systematic overestimation of speed. This area is also interesting to test discrimination of rocks and small ships. 67 targets were identified, and 23 detections were considered unreliable by SARTool©, as shown below.

Figure 15: SARTool map of targets

One should stress however that a number of targets detected on SAR images are in fact caused by ghost echoes are clearly visible (see Fig. 14). The technical reason for this has not been further investigated. SCOPE© allows further operator-driven classification, Fig.16 shows a zoom of the results of the targets classification (“still to be processed” in orange, « ship » in red, « undefined » in yellow or « other » in blue) is shown below. Many targets, close to the coasts (Guernsey island) did not seem to be ships but rather rocks, and were thus considered as « other » or « undefined » by the operator. 30 targets were classified “ship”, 50 “other” and 7 “undefined”. The quick look on the left of the image clearly represents a ship located at 2.632 °W and 49.813 °S. Its shape and heading are clearly visible.

Figure 16: SCOPE© display for echo classification

7. SMALL SHIP DETECTABILITY

According to theoretical results, the ability to detect small ships (15-18 meters) versus image resolution has been verified on several passes. The pass acquired on 20th August with good sea state conditions allowed for example three positive correlations illustrated in Fig. 17

Figure 17: Positive SAR/VMS correlations

8. OIL SPILL DETECTION IN IMAGE MODE

An oil slick (Fig.18) was also observed on another SAR image taken on August 20th, although the ENVISAT operating mode (IS6) was not the most appropriate for such detection. The fine resolution allows however to have good details of the slick and surrounding ships. To have a chance to identify potential polluter (Fig. 19 , shape and width of the

slick should be correlated with metocean conditions (Fig. 20 shows wind computed from the SAR Image by the SARTool© Wind retrieval module) and ship detection information combined with AIS or VMS, through forward and backtrack drift /ship trajectory modelling. Unfortunately in this case, the pollution was outside the AIS range, as reported by the MRCC.

Figure 18: Oil pollution in IS6 mode

Figure 19: Ship classification in IS6 mode

Fig 20: Wind map extraction

9. CONCLUSIONS AND PERSPECTIVES

MARISS trials performed in 2006 by CLS for the Maritime affairs have shown the following positive results:

•The service chain was operated as planned and audited by MARISS partner (Thales)

•SAR detection capability in Traffic Separation Scheme was successfully verified by Cross Jobourg MRCC,

potential polluter information transmitted to another MRCC (Cross Corsen) in a non optimal pollution detection mode , VMS coupling cases on small ships presented to a third MRCC (Cross Etel)

•SARTool© was successfully integrated in the chain and demonstrated a great potential for the ship detection application. They have also raised several perspectives of improvement:

•The acquisition chain performance is critical for the early warning capability of the service chain. However, some manual operations are still needed for echo classification, ambiguity removal, and often for parameter extraction. The MARISS test case has been used by Boost Technologies to include an automatic azimuth ambiguity removal function in the new version of SARTool.

•These tests have been used to evaluate the operationality of open ocean CLS service chain in boundary conditions: close to coastal areas with ragged coasts and using small vessels (half the SAR resolution size).

•For the improvement of the chain in this context, interest of an operational ancillary data service has been illustrated: sea state information for detection, metocean data for drift modelling, tidal service for echo discrimination in ragged coasts. On the other hand, SAR derived parameters such as heading; ship size and wind bring instantaneous information of great added value when in situ information is missing or suspicious. 10. ACKNOWLEDGEMENTS

The authors thank all operational members from the French Maritime Affairs for the provision of an operational assessment and of verification data for these tests. 11. REFERENCES

1. Detection, Classification and Identification of Marine Traffic from Space, State of the Art, version 2.1, DECLIMS consortium, November 2005